{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T05:45:46Z","timestamp":1743140746496,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819751273"},{"type":"electronic","value":"9789819751280"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5128-0_19","type":"book-chapter","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T23:02:31Z","timestamp":1720738951000},"page":"237-249","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive Score-Guided Mixup for\u00a0Medical Text Classification"],"prefix":"10.1007","author":[{"given":"Yuhong","family":"Pang","sequence":"first","affiliation":[]},{"given":"Yantuan","family":"Xian","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Xiang","sequence":"additional","affiliation":[]},{"given":"Yuxin","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"key":"19_CR1","unstructured":"Devlin, J., Chang, M., Lee, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis, Minnesota (2019)"},{"key":"19_CR2","unstructured":"Zhuang, L., Ya, S., Wayne, L.: A robustly optimized BERT pre-training approach with post-training. In: Proceedings of the 20th Chinese National Conference on Computational Linguistics, pp. 1218\u20131227. Chinese Information Processing Society of China, Huhhot, China (2021)"},{"key":"19_CR3","unstructured":"Zhang, H.Y., Cisse, M.: mixup: beyond empirical risk minimization. In: International Conference on Learning Representations (2018)"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1746\u20131751S. Association for Computational Linguistics, Doha, Qatar (2014)","DOI":"10.3115\/v1\/D14-1181"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Liu, Q.: Sentence-state LSTM for text representation. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, vol. 1, Long Papers, pp. 317\u2013327. Association for Computational Linguistics, Melbourne, Australia (2018)","DOI":"10.18653\/v1\/P18-1030"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Howard, J.: Universal language model fine-tuning for text classification. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 328\u2013339. Association for Computational Linguistics, Melbourne, Australia (2018)","DOI":"10.18653\/v1\/P18-1031"},{"key":"19_CR7","unstructured":"Guo, H., Mao, Y., Zhang, R.: Augmenting data with mixup for sentence classification: an empirical study. Augmenting Data with Mixup for Sentence Classification, arXiv:1905.08941 (2019)"},{"key":"19_CR8","unstructured":"Ray, C.H., Caragea, C.: Cross-lingual disaster-related multi-label tweet classification with manifold mixup. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pp. 292\u2013298. Association for Computational Linguistics, Online (2020)"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"He, J., Fu, M., Tu, M.: Applying deep matching networks to Chinese medical question answering: a study and a dataset. BMC Med. Inform. Decis. Making | Full Text, 91\u2013100 (2019)","DOI":"10.1186\/s12911-019-0761-8"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Zong, H., Yang, J., Zhang, Z., Li, Z., Zhang, X.: Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods. BMC Med. Inform. Decis. Making, pp. 1\u201312 (2021)","DOI":"10.1186\/s12911-021-01487-w"},{"key":"19_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/978-3-030-30490-4_19","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2019: Text and Time Series","author":"C He","year":"2019","unstructured":"He, C., Peng, L., Le, Y., He, J., Zhu, X.: SECaps: a sequence enhanced capsule model for charge prediction. In: Tetko, I.V., K\u016frkov\u00e1, V., Karpov, P., Theis, F. (eds.) ICANN 2019. LNCS, vol. 11730, pp. 227\u2013239. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30490-4_19"},{"key":"19_CR12","unstructured":"Vaswani, A., Shazeer, N.: Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 6000\u20136010. Curran Associates Inc, Red Hook, NY, USA (2017)"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Diao, S., Bai, J., Song, Y., Zhang, T.: ZEN: pre-training Chinese text encoder enhanced by n-gram representations. arXiv. 1911.00720 (2019)","DOI":"10.18653\/v1\/2020.findings-emnlp.425"},{"key":"19_CR14","series-title":"Lecture Notes in Electrical Engineering","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1007\/978-981-15-8599-9_60","volume-title":"Artificial Intelligence in China","author":"Y-J Li","year":"2021","unstructured":"Li, Y.-J., Zhang, H.-J., Pan, W.-M., Feng, R.-J., Zhou, Z.-Y.: Microblog rumor detection based on Bert-DPCNN. In: Liang, Q., Wang, W., Mu, J., Liu, X., Na, Z., Cai, X. (eds.) Artificial Intelligence in China. LNEE, vol. 653, pp. 524\u2013530. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-15-8599-9_60"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Shreyashree, S., Sunagar, P., Rajarajeswari, S.: BERT-based hybrid RNN model for multi-class text classification to study the effect of pre-trained word embeddings. Int. J. Adv. Comput. Sci. Appl. (2022)","DOI":"10.14569\/IJACSA.2022.0130979"},{"key":"19_CR16","doi-asserted-by":"publisher","unstructured":"Li, X., Zhang, Y., Jin, J., Sun, F., Li, N.: A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications (2023). https:\/\/doi.org\/10.1371\/journal","DOI":"10.1371\/journal"},{"key":"19_CR17","doi-asserted-by":"publisher","unstructured":"Shengbin, L., Fuqi, S.: A medical text classification approach with ZEN and capsule network. J. Supercomputing (2024). https:\/\/doi.org\/10.1007\/s11227-023-05612-6","DOI":"10.1007\/s11227-023-05612-6"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Pires, T., Schlinger, E.: How multilingual is multilingual BERT?. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 4996\u20135001. Association for Computational Linguistics, Florence, Italy (2019)","DOI":"10.18653\/v1\/P19-1493"}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5128-0_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T18:04:16Z","timestamp":1731953056000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5128-0_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819751273","9789819751280"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5128-0_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"12 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISBRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Bioinformatics Research and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kunming","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/bio.csu.edu.cn\/ISBRA2024\/ISBRA2024_Home.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}